This note book builds an end-to-end classification model uisng NLP, Naive Bayes.
1.Problem Identify whether the reviews of a restaurant made by customers are postive or negative.
2.Data The data is collected from
3.Evaluation Evaluation is done on basis of metrics like accuracy score.
4.Features Some information about data:
Entire data is in text format, so its better to use NLP for developing our ML models. Overall, we have 17000 reviews (combining both the datasets). We have two labels(columns) namely: Review : which is the review itself. Liked : which tells whether the review is positive or negative. 1 - for positive 0 - for negative Text language is english.